MENGURANGI UNCERTAINTY DI INDUSTRI KONSTRUKSI OFF-SHORE DENGAN PENDEKATAN THE LAST PLANNER SYSTEM (KAJIAN DI PT. XYZ)
DOI:
https://doi.org/10.24853/jisi.3.2.%25pAbstract
The field of decision-making in lean environment was not studied enough, and that inspired us to run more precise investigation in that area. Nowadays, with the implementation of lean in numerous companies all over the world, it is important to understand not only the truisms of lean, but also what impact does it have on sub processes of activities of the organization. As it is known, decisions are made by human and that means those decisions are influenced by many human factors. One of those factors is biases and framing effects, that had been closely studied by Noble prize winner Daniel Kahneman and his co-author Amos Tversky. They studied those effects from a point of view of economical psychology, yet not going into details. We took their work as a basis for our study of human biases and decision-making under uncertainty in off-shore industry. In this thesis, we try to take a closer look into three theories (lean planning, lean information flows and information in supply chain and decision-making under uncertainty). We connect them in order to achieve an understanding of how those aspects of organization’s activities are connected and how they influence on each other. This study was performed with two main goals in mind. The first goal was on one hand to understand and identify the main sources of uncertainty in the engineering process; and on the other hand to identify the main human biases that affect the decisions made in the engineering process. The second goal was to see the theoretical aspects of decision-making through the process of lean planning and lean information flows implementation and to identify ways to reduce the impact of the human bias on the decisions made.Results of this thesis are lean knowledge not sufficient, uncertainty can be handled better with lean, and overall improvement not enough. Human biases exist in engineering department are availability bias, representativeness bias, reliability bias and anchoring bias.To minimize the effect of biases can be done through multi process which involved many parties, such as six thinking hats technique, the premortem technique, checklists and memos. Besides that lean planning and the last planner system in the engineering process make the process having better certainty. Be on time, adapt to customer demand, inter-department coordination and information flow in general have been improved 25% after applied lean planning.Future research can be much more focus on evaluation and the way to handle human biases. Keyword: Human Bias, Lean Planning, The Last Planner System, decision making, uncertainty.Published
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